Factor Spotlight
Factor University

February 2017 Factor Review

2017's bull market continued in February, with Dividend Yield being the month's standout factor. The low volatility factor’s positive return in an up month is also quite notable. Even low beta stocks, which are expected to underperform when markets are up significantly, were basically flat. Book/Price was the laggard this month. And Momentum, the best performing factor in the latter half of the 20th century, has continued to lag.

Screen Shot 2017-03-14 at 4.05.29 PM.png
* Indicates a low – high polarity. Other factors have a high – low polarity.

One way to better understand these factors is to look at their beta to the S&P 500. Factors with a beta over 1 will generally be more volatile than the S&P 500. Factors with a beta of 1 have the same average volatility, while factors with a lower beta will move slightly less. Factors with a positive beta tend to move in the same direction as the market, while factors with a negative beta will generally move in the opposite direction.

When we look at beta from 2013 to present, Dividend Yield stands out for having a high positive beta and 12M Beta stands out for its significant negative beta.

Screen Shot 2017-03-14 at 5.06.12 PM.png

* Indicates a low – high polarity. Other factors have a high – low polarity.

Most of these betas are near-zero, which is part of their end appeal to the limited partners of quantitative investors - they're paying for returns that are minimally correlated to markets. But it's important to note that these betas are not stable. Market activity can cause them to spike up or down. To drive that point home, see below for how messy the one month rolling beta between various factors and the S&P 500 looks.

Screen Shot 2017-03-14 at 5.47.43 PM.png

While Dividend Yield's beta is consistently positive and 12M Beta is generally negative, most factors will switch between positive to negative beta. In 2014, Momentum had a positive beta to the market. In early 2016, it had a consistently negative beta, while today it is closer to zero. The spikes in these betas also represent time periods when incidental exposure to factors might catch fundamental portfolio managers off guard.

In upcoming posts, we will go over some of the concepts driving the new tools we are working on to quantify the effect of factor exposure.

As a reminder, Omega Point clients have access to regularly updated Factor Return data.


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